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Satellite imagery provides a dependable basis for computational models that aimed to determine actual evapotranspiration (ET) by surface energy balance. Satellite-based models enables quantifying ET over large areas for a wide range of applications, such as monitoring water distribution, managing irrigation and assessing irrigation systems’ performance. With the aim to evaluate the energy and water consumption of a large scale on-turn pressurized irrigation system in the district of Aguas Nuevas, Albacete, Spain, the satellite-based image-processing model SEBAL was used for calculating actual ET. The model has been applied to quantify instantaneous, daily, and seasonal actual ET over high- resolution Landsat images for the peak water demand season (May to September) and for the years 2006 – 2008. The model provided a direct estimation of the distribution of main energy fluxes, at the instant when the satellite overpassed over each field of the district. The image acquisition day Evapotranspiration (ET24) was obtained from instantaneous values by assuming a constant evaporative fraction (Λ) for the entire day of acquisition; then, monthly and seasonal ET were estimated from the daily evapotranspiration (ETdaily) assuming that ET24 varies in proportion to reference ET (ETr) at the meteorological station, thus accounting for day to day variation in meteorological forcing. The comparison between the hydrants water consumption and the actual evapotranspiration, considering an irrigation efficiency of 85%, showed that a considerable amount of water and energy can be saved at district level.

Among indirect estimations of the soil water content in the upper layer, the "triangle method" is based on the relationship between the optical and thermal features sensed via Earth Observation. These features are controlled by water content at surface and within root zone, but also by meteorological forcing including air temperature and humidity, and solar radiation. Night and day-time MODIS composite land-surface temperature (LST) allowed applying the thermal admittance version of the method; by taking into account the temporal admittance of the soil, this version was previously found achieving high accuracy in estimate the soil water content at high spatial resolution within a short time period (a single irrigation season). In this study, the method has been applied on a long time series to analyse the seasonal influence of the meteorological forcing on the triangle method index (or temperature vegetation index, TVX). The Imera Meridionale hydrological basin (≈ 2000 km2, Sicily) has been chosen to test the method over a decade time series, since its climate varies during the year from arid to temperate. The climate is arid for ≈3-7 months (from April-May to August- October) depending on altitude. The temporal analysis reveals that NDVI and LST pairs moves circularly within the optical and thermal diachronic feature space. Concordantly, the boundaries of the triangle move during the seasons. Results suggest that the contribution of soil water content fluctuations need to be isolated from other environmental stress factors, or at least, the conceptual meaning of TVX have to be better interpreted.

Temporal availability of grapes actual evapotranspiration is an emerging issue since vineyards farms are more and more converted from rainfed to irrigated agricultural systems. The manuscript aims to verify the accuracy of the actual evapotranspiration retrieval coupling a single source energy balance approach and two different temporal upscaling schemes. The first scheme tests the temporal upscaling of the main input variables, namely the NDVI, albedo and LST; the second scheme tests the temporal upscaling of the energy balance output, the actual evapotranspiration. The temporal upscaling schemes were implemented on: i) airborne remote sensing data acquired monthly during a whole irrigation season over a Sicilian vineyard; ii) low resolution MODIS products released daily or weekly; iii) meteorological data acquired by standard gauge stations. Daily MODIS LST products (MOD11A1) were disaggregated using the DisTrad model, 8-days black and white sky albedo products (MCD43A) allowed modeling the total albedo, and 8-days NDVI products (MOD13Q1) were modeled using the Fisher approach. Results were validated both in time and space. The temporal validation was carried out using the actual evapotranspiration measured in situ using data collected by a flux tower through the eddy covariance technique. The spatial validation involved airborne images acquired at different times from June to September 2008. Results aim to test whether the upscaling of the energy balance input or output data performed better.

Chlorophyll-a (CHL-a) and Sea Surface Temperature (SST), amongst others, are proxies or indicators for water quality and can be easily retrieved synoptically and almost in near-real time through satellite remote-sensing. However, as they evolve in space and time in response to winds and currents, a full resolution of the temporal and spatial scales of these latters is required and their influence in shaping the distribution of water quality parameters needs to be assessed. While providing synoptic views and revealing mesoscale features, satellites suffer, indeed, from inadequate representation of sub-grid physical processes and lack of temporal resolution. Conventional point-wise measurements provide data to study high-frequency motions such as tides or high-frequency wind-driven circulation, lacking on the other hand of the spatial resolution required to resolve their spatial variability. We show here that a combined use of near-surface currents, available through High-Frequency (HF) radars, and satellite data (e.g., TERRA and AQUA/MODIS, VIIRS/NPP), are complementary tools as they help solving both fine-scale structures, especially at the coastal boundaries where satellite imageries lack of the required resolution, as well as satellite-derived mesoscale structures are fundamental aid to understand and interpret finer-scale structures in terms of larger-scale ocean dynamics.

An operational use of the actual evapotranspiration estimates requires the integration from instantaneous to daily values. This can commonly be achieved under the hypothesis of daytime self-preservation of the evaporative fraction. In this study, it has been evaluated the effect of this assumption on the assessment of daily evapotranspiration from proximity sensing images acquired at hourly intervals over a homogeneous olive groove. Results have been validated by comparison with observations made by a micrometeorological (EC-flux tower) and an eco-physiological (sap flux) sensor. SEBAL model has been applied to thermal and multispectral images acquired during a clear day on August 2009 trough a FLIR A320G thermal camera and a Tetracam MCA II multispectral camera, installed on a tethered helium balloon. Thermal and multispectral images were characterized by very high spatial resolution. This experiment aims to analyze two effects: 1) the consistency of the self-preservation hypothesis for daily estimates of the actual evapotranspiration from hourly assessments at different times of the day; 2) the effects of the spatial resolution on the performances of the energy balance model. To evaluate the effects of the spatial resolution, semi-hourly observations made by a flux tower and sap-flow measures were compared to the evapotranspiration estimates performed using downscaled images at resolutions close to canopy sizes (2, 5 and 10 m). Results show that the best estimates are obtained with a spatial resolution comparable to the average size of the canopy with images taken approximately at 10 UTC.

This paper reports the first results of the Project SESAMO - SistEma informativo integrato per l’acquisizione, geStione e condivisione di dati AMbientali per il supportO alle decisioni (Integrated Information System for the acquisition, management and sharing of environmental data aimed to decision making). The main aim of the project is to design and develop an integrated environmental information platform able to provide monitoring services for decision support, integrating data from different environmental monitoring systems (including WSN). This ICT platform, based on a service-oriented architecture (SOA), will be developed to coordinate a wide variety of data acquisition systems, based on heterogeneous technologies and communication protocols, providing different sort of environmental monitoring services. The implementation and validation of the SESAMO platform and its services will involve three specific environmental domains: 1) Urban water losses; 2) Early warning system for rainfall-induced landslides; 3) Precision irrigation planning. Services in the first domain are enabled by a low cost sensors network collecting and transmitting data, in order to allow the pipeline network managers to analyze pressure, velocity and discharge data for reducing water losses in an urban contest. This paper outlines the SESAMO functional and technological structure and then gives a concise description of the service design and development process for the second and third domain. Services in the second domain are enabled by a prototypal early warning system able to identify in near-real time high-risk zones of rainfall-induced landslides. Services in the third domain are aimed to optimize irrigation planning of vineyards depending on plant water stress.

The paper reports a critical analysis of the thermal inertia approach to map surface soil water content on bare and sparsely vegetated soils by means of remotely sensed data. The study area is an experimental area located in Barrax (Spain). Field data were acquired within the Barrax 2011 research project. AHS airborne images including VIS/NIR and TIR bands were acquired both day and night time by the INTA (Instituto Nacional de Tecnica Aeroespacial) between the 11 th and 13 rd of June 2011. Images cover a corn pivot surrounded by bare soil, where a set of in situ data have been collected previously and simultaneously to overpasses. To validate remotely sensed estimations, a preliminary proximity sensing set up has been arranged, measuring spectra and surface temperatures on transects by means of ASD hand-held spectroradiometer and an Everest Interscience radiometric thermometer respectively. These data were collected on two transects: the first one on bare soil and the second from bare to sparsely vegetated soil; soil water content in both transects ranged approximately between field and saturation values. Furthermore thermal inertia was measured using a KD2Pro probe, and surface water content of soil was measured using FDR and TDR probes. This ground dataset was used: 1) to verify if the thermal inertia method can be applied to map water content also on soil covered by sparse vegetation, and 2) to quantify a correction factor of the downwelling shortwave radiation taking into account sky cloudiness effects on thermal inertia assessment. The experiment tests both Xue and Cracknell approximation to retrieve the thermal inertia from a dumped value of the phase difference and the three-temperature approach of Sobrino to estimate the phase difference spatial distribution. Both methods were then applied on the remotely sensed airborne images collected during the following days, in order to obtain the spatial distribution of the surface soil moisture on bare soils and sparse vegetation coverage. Results verify that the thermal inertia method can be applied on sparsely vegetated soil characterized by fractional cover up to ~0.25 (maximum value within this experiment); a lumped value of the phase difference allows a good estimate of the thermal inertia, whereas the comparison with the three-temperature approach did not give conclusive responses because ground radiometric temperatures were not acquired in optimal conditions. Results also show that clear sky only at the time of the remote sensing acquisitions is not a sufficient condition to apply the thermal inertia method. A corrective coefficient taking into account the actual sky cloudiness throughout the day allows accurate estimates of the spatial distribution of the thermal inertia (r 2 ~ 0.9) and soil water content (r 2 ~ 0.7).

During floods following rainfall events characterized by long return period, rivers bring to their mouths the higher concentration of sediments. This paper deals with a qualitative assessment of coastal water and turbidity load in estuarine waters as a consequence of an intense rainfall event occurred on the 16t h and 17 th September 2003 in the eastern part of Sicily. Although empirical relationships to estimate turbidity using remote sensing can be found in literature, however models parameters need to be calibrated through in situ measures acquired via intensive field campaigns. The algorithm used within this research was calibrated using field data acquired during three periods in 2008 (at the beginning of July, August and September). Plumes caused by two rivers, the Simeto and Anapo, were spatially and temporally analyzed. The rivers belong to two catchments characterized by different pedology and land cover. It was proved that the turbidity plume at the estuary has a strict correlation with distance from river mouth, however it strongly depends on catchment characteristics. A multitemporal analysis of MODIS images with 250 m spatial resolution showed that nephelometric turbidity (NT) rises as the flow discharge reaches the gulf, then it sharply decreases tending to an asymptotic base value approximately after a decade. Finally, the coarse spatial resolution of MODIS images was judged not appropriate to characterize plume dynamic close to the mouths of the rivers under investigation.

The knowledge of spatial and temporal variability of land cover is important to manage water resources for yield forecasting, water stress prediction, irrigation water management and flood protection. Cloud cover dramatically reduces the temporal resolution of optical data thus limiting their operational use; in addition, the spatial resolution is often inadequate for applications in heterogeneous areas. On the other hand, algorithms based on Synthetic Aperture Radar (SAR) implemented to retrieve vegetation parameters are not yet fully validated. New SAR missions (COSMO-Skymed and Terrasar-X) may represent a suitable source of data for operational uses due to the high spatial and temporal resolution, although X band is not optimal for agricultural and hydrological applications. This paper reports the influence of soil-vegetation variables (especially biomass indices) on X-band COSMO-Skymed data using Ping Pong products. The study is carried out over two different sites: the SELE plain (in the south-eastern part of Campania, Italy) that is mainly characterized by herbaceous plants and tree crops; and the Campobello-Castelvetrano area (in the south-western part of Sicily, Italy) mainly covered by olive trees, vineyards and woods. The sensitivity analysis is performed by comparing vegetation indices (NDVI or LAI) derived by Landsat TM 5 and ETM+ 7 with COSMO-Skymed (CSK) images acquired in May-June 2010 within the project COSMOLAND (Use of COSMO-SkyMed SAR data for LAND cover classification and surface parameters retrieval over agricultural sites) funded by the Italian Space Agency (ASI). Sensitivity analysis results address to develop algorithms to retrieve vegetation biomass maps from CSK X band characterized by high temporal and spatial resolution.

Agricultural water requirement in arid and semi-arid environments represents an important fraction of the total water consumption, suggesting the need of appropriate water management practices to sparingly use the resource. Furthermore the quality and quantity of some crops products, such as grape, is improved under a controlled amount of water stress. The latter is related, on a side to actual evapotranspiration (ET) through water demand, on the other side to plant water content through leaf water potential. Residual energy balance approaches based on remote sensing allow to estimate the spatial distribution of daily actual ET at plant scale, representing an useful tool to detect its spatial variability across different cultivars and even within each parcel. Moreover, the connection between actual ET and leaf water potential is still not well assessed, especially under water stress conditions, even if farmers use leaf water potential to plan irrigation. However residual energy balance methods are based on the hypothesis that storage terms are negligible, at least during the remote sensor overpass. Indeed, energy balance approaches estimate daily actual ET from the instantaneous value at the overpass time using a daily integration method. The paper first verifies this latter assumption using field data acquired by a flux tower on a whole phenological period. Then, the actual ET values measured by eddy covariance tower were analyzed together with water potential measured using a Scholander chamber; the analysis highlights that, under water stress conditions, daily actual ET is inversely linearly related with water potential. These results suggest the possibility to use remote sensing-based ET as support for irrigation management at plot scale.

Soil humidity plays a key-role in hydrological and agricultural processes. In the rainfall-runoff processes the knowledge of its spatial distribution is fundamental to accurately model these phenomena. Furthermore in agronomy and agricultural sciences, assessing the water content of the root zone is required in order to optimize the plant productivity and to improve the irrigation systems management. Despite the importance of this variable the in situ measurements techniques based on Time Domain Reflectometry (TDR) or on the standard thermo-gravimetric methods, are neither cost-effective nor representative of its spatial and temporal variability. Indirect estimations via Earth Observation (EO) images include the triangle method, which shows that Land Surface Temperature (LST) is prevalently controlled by surface and root zone humidity in bare and vegetated soils respectively. The effects of pre-processing techniques correcting for altimetry and seasonality are analyzed by means of shortwave and longwave airborne images acquired on a vineyard during a whole phenological period. The paper also discusses the advantages induced by replacing the absolute temperatures with relative values, that were obtained subtracting the temperatures measured by micrometeorological station or the surface temperature of high thermal inertia surfaces (as small irrigation reservoir) chosen as reference values. The validation with in situ data also highlights that a higher spatial resolution not necessarily imply a higher accuracy.

The severe erosion phenomena affecting the Mediterranean coasts are strictly related to geophysical characteristics and socio-economic pressures. This suggests the need of monitoring and modelling the phenomenon in order to quantify its strength. In fact, the shoreline position, as well as its temporal evolution, provides important information for designing defence structures and for the development of a coastal management plan. The shoreline has a dynamic nature as it changes both in the short and long period. Those changes are caused by geo-morphological (e.g. bars and barrier island development etc.) and hydrodynamic (wave motion, tides and flows) processes, as well as by sudden and fast events such as sea storms, earthquakes and tsunamis. The research examines the uncertainty in positioning the shoreline coupling remotely sensed images and a hydro-maritime model. Although the assessment accuracy strongly relies on data availability and consistency, the resulting assessment of the shoreline erosion and accretion is crucial for an overall understanding of the hydro-maritime geo-morphological interaction. The study case is the Marsala coastline (western coast of Sicily, Italy), named 12th island physiographic unit. It is characterized by a low coast with sandy sediments from Holocene age. These sediments are in continuity of sedimentation on whitish debris composed by organogenic limestone from Pleistocene age. The diachronic analysis was carried out on both emerged and submerged parts of the beach and involves two distinct phases. In the first phase, geo-morphological in situ data have been compared with maps and georeferenced remote sensing images referred to the period 1994-2006. It allowed the identification of shoreline indicators [2] such as the beach cross-section and the shoreline positioning including its spatial and temporal variations. It should be noted that the comparison between EO (Earth Observation) images and cartographic maps is subjected to several uncertainties, due to graphic error, geo-referencing accuracy and spatial resolution. Moreover tidal and climate waves data refer to an acquisition time different to that of the EO images. In the second phase, a maritime hydraulic modelling accounting for sea fluctuations has been performed. The run-up is related to wave's amplitude and phase, as well as to the composition and particle size of the beach sediments determining the beach slope [3]. Prior to run-up calculation, an investigation aiming to evaluate how the waves propagate from offshore to inshore (a third-generation spectral wave numerical model, SWAN - Simulating WAves Nearshore), has been carried out. Wave data have been acquired by a buoy belonging to the National Network Waves Data, located at the SW of the Mazara del Vallo harbour (Trapani), while tide data were recorded by the national marigraph of Porto Empedocle (Agrigento). The results allowed assessing the uncertainty and the consequent accuracy in the shoreline positioning for given slope, highlighting that it is not always possible to assess the shoreline rise and fall, for values lower than 10-15 m.

In the last years, the availability of new technologies of Earth Observation encouraged researches to use integrated approaches for environmental monitoring. Even for agro-hydrological applications, remotely sensed data are available on wide areas allowing the retrieval of cost-effective and representative estimation of high spatial and temporal variability of the soil-vegetation system variables. In particular, soil water content plays an important role determining the partition of precipitation between surface runoff and infiltration and, moreover, influences the distribution of the incoming radiation between latent and sensible heat flux. As a consequence, distributed soil water content maps are essential data for watershed applications such as flood prediction and crop irrigation scheduling. Since cloud cover has been highlighted as the main limitation of SW/TIR traditional techniques, this research is focused on the applicability of soil moisture models based on active microwave. In particular, a Semi Empirical Coupled Model (SECM) is proposed. Reliable assessments of both surface roughness and dielectric constant (thus soil moisture) are retrieved by means of two iterative modules, without any calibration phase. The validation with in situ soil moisture, taken at a depth comparable to the RADAR penetration, gives a good agreement for bare-sparse vegetation coverage. The research is carried out on the 24 km² test-site of DEMMIN (Gormin farm, Mecklenburg Vorpommern), in the North-East of Germany. Data were acquired within the ESA-funded AgriSAR project, between April and July 2006. The implemented model uses HH, VV and HV polarized L-bands, acquired by the German Aerospace Center (Deutsches Zentrum fur Luft- und Raumfahrt - DLR) using an airborne platform.

Soil moisture is difficult to quantify because of its high spatial variability. Consequently, great efforts have been undertaken by the research community to develop practical remote sensing approaches to estimate the spatial distribution of surface soil moisture over large areas and with high spatial detail. Many methodologies have been developed using remote sensing data acquiring information in different parts of the electromagnetic spectrum. Conventional field measurement techniques (including gravimetric and time-domain reflectometry) are point-based, involve on-site operators, are time expensive and, in any case, do not provide exhaustive information on the spatial distribution of soil moisture because it strongly depends on pedology, soil roughness and vegetation cover. The technological development of imaging sensors acquiring in the visible (VIS), near infrared (NIR) and thermal infrared (TIR), renewed the research interest in setting up remote sensed based techniques aimed to retrieve soil water content variability in the soil-plant-atmosphere system (SPA). In this context different approaches have been widely applied at regional scale throughout synthetic indexes based on VIS, NIR and TIR spectral bands. A laboratory experiment has been carried out to verify a physically based model based on the remote estimation of the soil thermal inertia, P, to indirectly retrieve the soil surface water content, θ. The paper shows laboratory retrievals using simultaneously a FLIR A320G thermal camera, a six bands customized TETRACAM MCA II (Multiple Camera Array) multispectral camera working in the VIS/NIR part of the spectrum. Using these two type of sensors a set of VIS/NIR and TIR images were acquired as the main input dataset to retrieve the spatial variability of the thermal inertia values. Moreover, given that the accuracy of the proposed approach strongly depends on the accurate estimation of the soil thermal conductivity, a Decagon Device KD2 PRO thermal analyzer was used to verify the remotely estimate of thermal conductivity. Remotely estimated water contents were validated using the gravimetric method. The considered thermal inertia approach allowed prediction of the spatial distribution of the soil water with a satisfactory level of accuracy.

Daily high spatial resolution assessment of actual evapotranspiration is essential for water management and crop water requirement estimation under stress conditions. The application of energy balance models usually requires satellite observations of radiometric surface temperat ure with high geometrical and temporal resolutions. By now, however, high spatial resolution (~ 100 m) is available with low time fre quency (approximately every two weeks); at the opposite daily acquisition are characterised by poor spatial resolution. The analysis of vegetation index (VI) and land surface temperature (LST) spatial relationship, shows in substance a scale invariant behaviour [1] ; this consideration allows the application of spatial sharpening algorithms of thermal data, by means of a combination of high spatial resolution data in VIS/NIR range with high temporal acquisition on TIR. In this paper, a sharpening algorithm was applied using the thermal bands of MODIS ( MOderate resolution Imaging Spectroradiometer ) and vegetation indices derived by ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer ) sensor; the choice of this sensors is justified by the simultaneous acquisition time. The results of this sharpening process was firstly compared against LST estimation (at the same spatial resolution) by means of the ASTER simultaneous data; then the derived high spatial resolution LST distribution was used in order to investigate the effect of the disaggregation on the outputs of surface energy balance models. The above described application was performed on a Sicilian study area. Keywords: land surface temperature, disaggregation, actual ev apotranspiration, surface energy balance models.

During the last the two decades, the scientific community developed detailed mathematical models for simulating land surface energy fluxes and crop evapotrans piration rates by means of a energy ba lance approach. These models can be applied in large areas and with a spatial distributed approach using surface brightness temperature and some ancillary data retrieved from satellite/airborne remote sensed imagery. In this paper a district scale application in combination with multispectral (LandaSat 7 TM data) and hyperspectral airborne MIVIS data has been carried out to test the potentialities of two different energy balance models to estimate evapotranspiration fluxes from a set of typical Mediterranean crops (wine, olive, citrus). The impact of different spatial and radiometric resolutions of MIVIS (3m x 3m) and LandSat (60m x 60m) on models-derived fluxes has been investigated to understand the roles and the main conceptual differences between the two models which respec tively use a “single-layer” (S EBAL) and a “two-layer”(TS) schematisation. Keywords: actual evapotranspiration, spatial resolution, surface energy balance.